A typical wireless network comprises a plurality of mobile terminals, each in radio communication with an access point or base station of the network. The access points may also be in communication with a central controller that in turn may have a link to other networks, for example a fixed Ethernet-type network. Until recently considerable effort was put into designing systems so as to mitigate for the perceived detrimental effects of multipath propagation, especially prevalent in wireless LAN (local area network) and other mobile communications environments. However the described work G. J. Foschini and M. J. Gans, “On limits of wireless communications in a fading environment when using multiple antennas” Wireless Personal Communications vol. 6, no.3, pp.311-335, 1998 has shown that by utilising multiple antenna architectures at both the transmitter and receiver, a so-called multiple-input multiple-output (MIMO) architecture, vastly increased channel capacities are possible. Attention has also turned to the adoption of space-time coding techniques for wideband channels. Typically channel state information (CSI) for detection of such coding is acquired via training sequences and the resulting CSI estimates are then fed to a space-time decoder along with the received signal.
A particular problem arises in a communications link where a transmitter with more than one transmit antenna is employed, since signals received from different transmit antennas interfere with one another. This results in so-called multi-stream interference (MSI) and causes decoding difficulties. The potential advantage, however, is greatly increased throughput (that is, a higher bit rate) for such a communications link. In this type of MIMO (Multiple-input Multiple-output) communication link the “input” (to a matrix channel) is provided by the transmitter's plurality of transmit antennas and the “output” (from a matrix channel) is provided by a plurality of receive antennas. Thus each receive antenna receives a combination of signals from all the transmitter's transmit antennas which must be unscrambled.
FIG. 1 of the accompanying drawings is a schematic diagram illustrating a typical MIMO communication system 1 comprising a transmitting device 2 and a receiving device 14. In the transmitting device 2, a data source 4 provides an information symbol vector d to a MIMO encoder 8 which encodes the symbol vector d as T code symbols x1 x2 . . . , xT. The T code symbols x1 x2 . . . , xT can be represented as transmit symbol vector x, and in this example, T is three. The T code symbols x1 x2 . . . , xT are then transmitted separately and simultaneously from T transmit antennas 6 respectively. An example of a MIMO encoder 8 is found by a direct mapping of input symbol di to output symbol xi.
In the receiving device 14, a plurality R of receive antennas 18 receives respectively signals y1, . . . , yR, represented as symbol vector y. For a narrowband channel the channel response of the channel 12 between the transmitting device 2 and the receiving device 14 are represented by an R×T channel response matrix H (having R rows and T columns of complex channel coefficients), with the noise contribution at the receiver being represented by the R-dimension noise vector v. Using this model,y=Hx+v.  (1)
The receive signals y are then input to a MIMO detector and decoder 16, along with an estimate of the channel response matrix, H. Channel estimation in the MIMO detector 16 can be achieved in a number of well-documented ways. These inputs to the MIMO detector 16 can be used to form an estimate {circumflex over (x)} of the transmit symbol vector, or to directly form an estimate of the information symbol vector d. An example MIMO detector 16 corresponding to the example encoder described above is to generate a linear estimator matrix W equal to H−1, so that the estimate {circumflex over (x)} of the transmit symbol vector is given by:{circumflex over (x)}=Wy.  (2)
This estimate {circumflex over (x)} of the transmit symbol vector is then decoded by the MIMO decoder 16 by performing the reverse of the encoding operation performed by the MIMO encoder 8 to produce an estimate {circumflex over (d)} of the original information symbol vector d, and this estimate {circumflex over (d)} is passed to the data destination 22.
In the example above, the linear estimator matrix W effectively separates the plurality of transmitted signals arriving at the receive array. Non-linear estimators are more optimal and may employ maximum likelihood (ML) or maximum a posteriori probability (MAP) estimation techniques.
In the above example, data transmission over the channel 12 from multiple users can be handled using time division multiplexing in combination with the spatial multiplexing of MIMO so that the sequence of operations above is performed in one time frame for one user and for another user in the next time frame.
When the channel is frequency selective, this can be handled by using the OFDM (Orthogonal Frequency Division Multiplexing) technique. With standard OFDM there are a number (say, N) of overlapping tones (or sub-carriers). The bit stream is split into N parallel data streams at a rate of 1/N of the original rate. Each stream is modulated onto a unique tone and then combined to a single signal for transmission from a single antenna by means of an N-point inverse Fast Fourier Transform (IFFT). The tones are orthogonal with adjacent ones and so do not interfere. Each block of N samples output from the IFFT is known as an OFDM symbol. A fixed number of additional samples are copied from the end of each OFDM symbol and pre-pended to it. This is known as a cyclic prefix (CP). Because this CP is designed to be longer than the greatest delay of the multipath channel response, inter symbol interference (ISI) is eliminated and the data on each sub-carrier experiences a narrowband flat fading channel response.
A combined MIMO-OFDM system would operate similarly to the basic OFDM system described above where the system model for each sub-carrier can be expressed using equation (1) above. For each sub-carrier a different symbol vector, x, would be transmitted, a different signal vector, y, would be received, and a different channel response matrix, H, would be experienced. For example, if there were N sub-carriers, N MIMO-encoded transmit vectors would be generated. The N symbols corresponding to the first transmit antenna would be input to an IFFT and an OFDM symbol for the first transmit antenna created. This process would be repeated for each transmit antenna. The resultant T OFDM symbols would then be transmitted simultaneously over the multiple antennas of the MIMO system.
Third generation mobile phone networks use a form of multiplexing known as CDMA (Code Division Multiple Access) spread spectrum signals for communicating across the radio interface between a mobile station and a base station. These 3G networks are encompassed by the International Mobile Telecommunications IMT-2000 standard. Collectively the radio access portion of a 3G network is referred to as UTRAN (Universal Terrestrial Radio Access Network) and a network comprising UTRAN access networks is known as a UMTS (Universal Mobile Telecommunications System) network. The UMTS system is the subject of standards produced by the Third Generation Partnership Project (3GPP, 3GPP2), technical specifications for which can be found at www.3gpp.org. Fourth generation networks, although not yet defined, may employ MIMO-based techniques.
Multi-Carrier Code Division Multiple Access (MC-CDMA) is similar to OFDM, but data symbols are first spread as for CDMA with a spreading code having a spreading factor SF (representing the number of chips per data bit). Multiple users can therefore be supported by each user employing a different spreading code. The SF chips are then allocated to SF adjacent sub-carriers of an OFDM system, i.e. with no spreading in time. This can result in the loss of orthogonality between spreading codes at a receiver, as each sub-carrier experiences a different channel gain. However, the use of a suitable CP, as for ordinary OFDM, eliminates inter symbol interference (ISI).
Orthogonal Frequency Code Division Multiplexing (OFCDM) is similar to MC-CDMA, but the chips resulting from spreading a single symbol can be arranged in blocks of frequency and time, so that each data symbol is allocated to a number of sub-carriers and a number of OFDM symbols on those sub-carriers. The dimensions of the block can be altered, for example the spreading can be SF in time and 1 in frequency, or vice versa, or some other combination making up SF chips. This is illustrated in FIG. 2 of the accompanying drawings. In the example of FIG. 2, the overall spreading factor SF illustrated in the left-most portion is allocated with a spreading factor SFtime in the time domain and SFfreq in the frequency domain, as illustrated in the middle portion of FIG. 2. As illustrated in the right-most portion of FIG. 2, the chips of the first symbol (Symbol 1) of user data are allocated across the first SFfreq subcarriers and the first SFtime OFDM symbols. The next symbol (Symbol 2) of user data is spread and allocated in a similar way, being allocated to the next SFfreq subcarriers and the same SFtime OFDM symbols. This is repeated until all the subcarriers are filled with the user's data (with Symbol K occupying the final SFfreq subcarriers). The SFtime OFDM symbols can then be transmitted, and the next SFtime OFDM symbols can then be allocated and transmitted in the same way. Thus a single user data fills all subcarriers (N/SFfreq must be an integer, in this example equal to K). In the right-most portion of FIG. 2, the allocation is schematically shown as SFfreq=5 and SFtime=8 by the grid division illustrated within each symbol. MC-CDMA can be described as an OFCDM system where symbols are always spread by a factor of SF in frequency and 1 in time.
As an alternative to the usual OFCDM scheme described above in which spreading is carried out first and the resulting chips then allocated to the time and frequency domains as in FIG. 2, time and frequency spreading can be carried out sequentially. A time spreading code of length SFtime (the time spreading factor) would indicate both the amount of spreading in the time domain (indicated by SFtime) and the form of spreading (indicated by the type of time spreading code). A frequency spreading code having a frequency spreading factor SFfreq would indicate the amount of spreading to be performed in the frequency domain, or the number of frequency sub-carriers across which the data symbol is to be spread.
FIG. 3 of the accompanying drawings shows how the MIMO communication system 1 of FIG. 1 can be modified to enable data from multiple users to be multiplexed according to the OFCDM scheme. To simplify the explanation, only the data from a single user will be illustrated; the data from other users is spread in frequency and time in a corresponding way and combined onto the same transmit signals described below.
As for the MIMO system of FIG. 1, in the transmitting device, a data source 4 provides an information symbol vector d to a MIMO encoder 8 which encodes the symbol vector d to a T-dimensional symbol vector x. Unlike in the MIMO system of FIG. 1, in the MIMO-OFCDM system of FIG. 3, the symbol vector x is then processed by an OFCDM spreading portion 10 before transmission. The symbol vector x is spread in time to give a T×SFtime transmit chip matrix X (T rows and SFtime columns), where SFtime is the spreading factor in the time dimension. The transmit chip matrix X is also spread across SFfreq adjacent frequency sub-carriers as described above and the various sub-carriers combined before transmission over the T transmit antennas 6.
The response of the channel 12 between the transmitting device 2 and the receiving device 14, for a single sub-carrier, is again represented by a R×T channel response matrix H (R rows and T columns), with the noise contribution now being represented by a R×SFtime matrix V.
Using the above channel model, the R×SFtime chip matrix Y received at the receiving device 14, can be represented as:Y=HX+V. 
The received signals Y are then input to a MIMO detector 16-1. As before, the MIMO detector 16-1 requires an estimate of the channel response matrix, H, which can be obtained using methods well known to someone skilled in the art. An example MIMO detector 16-1 is to generate a linear estimator matrix W equal to H−1 so that the estimate {circumflex over (X)} of the transmit chip matrix is given by:{circumflex over (X)}=WY.
This is performed separately for each sub-carrier. The estimates {circumflex over (X)} of the transmit chip matrix for each sub-carrier are then passed to an OFCDM despreading portion 20 which performs the reverse of the spreading performed by the OFCDM spreading portion 10, resulting in an estimate {circumflex over (x)} of the T-dimension symbol vector x. This estimate is then decoded by the MIMO decoder 16-2 by performing the reverse of the encoding operation performed by the MIMO encoder 8 to produce an estimate {circumflex over (d)} of the original data symbol vector d, and this estimate {circumflex over (d)} is passed to the data destination 22.
Practical MIMO systems can benefit from the selection and use of a set of antennas from a total greater than the number of transmit and/or receive hardware chains. If, for example, a system had four transmit and four receive radio frequency (RF) chains, but had eight antennas available at each end, it could choose which four out of the eight antennas would give it the best performance. This allows hardware (space, cost and power) savings to be made, since only four transmit and four receive RF chains would be required to be built, whilst still gaining some of the benefits of having a larger number of antennas. The only duplication is the antenna elements themselves (which are relatively low cost), and the small overhead introduced by the additional RF switching (which is still more economical than multiple transmit and receive chains). This use of antenna subset selection could be employed at the transmitter, the receiver, or both.
Various methods have been proposed as to how a system would decide what the best subset of antennas is. For example, in “MIMO antenna subset selection with space-time coding”, D. A. Gore and A. J. Paulraj, IEEE Trans. Signal Processing, Vol. 50, No. 10, October 2002, pp. 2580-2588, two cases are differentiated based on the type of channel knowledge used in the selection process. In the first case, the antenna subsets are selected based on exact channel knowledge (ECK). In the second case, statistical channel knowledge (SCK) is employed by the selection algorithm. When ECK is available, it is shown that the selection algorithm chooses the antenna set that maximizes the channel Frobenius norm leading to both coding and diversity gain.
When SCK is available, the selection algorithm chooses the antenna set that maximizes the determinant of the covariance of the vectorized channel leading mostly to a coding gain.
In “Antenna selection for spatial multiplexing systems based on minimum error rate”, R. W. Heath and A. Paulraj, in Proc IEEE ICC, 2001, pp. 2276-2280, spatial multiplexing with multiple antennas is employed at both the transmitter and receiver to take advantage of large capacity gains. A criteria for selecting the optimal antenna subset is presented in terms of minimum error rate, when coherent receivers, either linear or maximum likelihood (ML), are used over a slowly varying channel. For the ML receiver the subset whose output constellation has the largest minimum Euclidean distance is picked. For the linear receiver post-processing SNRs (signal to noise ratios) of the multiplexed streams is used whereby the antenna subset that induces the largest minimum SNR is chosen.
In packet-based communication systems, some packets will be received incorrectly, or not received at all. When this is recognised by the receiver, through a mechanism such as verifying cyclic redundancy code (CRC) check bits, a NACK (Negative Acknowledgement) packet is sent back to the transmitter, in order to instruct it to retransmit the lost or corrupted packet. In a Hybrid-ARQ (Hybrid Automatic Repeat request, H-ARQ) system, there are different methods by which this retransmission can occur. One method is to retransmit exactly the same packet as was initially sent, and allow the receiver to either decode the second packet alone, or combine it with the first packet to improve the signal to noise ratio (Chase combining). Another method is for the transmitter to alter the puncturing of the output from its channel encoder for the second packet so that different parity bits are transmitted. Whilst this allows the second packet to be decoded in isolation from the first packet (if this is required for some reason), the data from the two packets can be combined so that the decoder has an increased number of parity bits for each transmitted information bit (known as incremental redundancy).
The direct application of the above H-ARQ methods (Chase combining and incremental redundancy) to MIMO systems has been considered in “The performance of BLAST with hybrid ARQ in Ricean fading channels”, H. Zheng, in Proc. IEEE VTC, October 2001, pp. 901-904.
The performance of MIMO systems with H-ARQ can be improved by modifying the retransmitted packet in different ways, and one such method for doing so is reported in “Hybrid ARQ protocols using space-time codes”, A. Van Nguyen and M. A. Ingram, in Proc. IEEE VTC, October 2001, pp. 2364-2368. In this paper, the performance of space-time codes (STCs) in a pure ARQ protocol (ST-ARQ) is first examined. Two hybrid ARQ schemes using STC are then proposed: space-time hybrid ARQ (ST-HARQ) and turbo space-time hybrid ARQ (TST-HARQ). For the ST-HARQ scheme, the previous transmitted packets are combined with the current received packet. In this scheme, the diversity gain is increased with every retransmission resulting in a higher probability of an accepted packet. For the TST-HARQ scheme, the transmitted packets are code combined and iteratively decoded.
Another such method is reported in “Hybrid ARQ transmission and combining for MIMO systems”, E. N. Onggosanusi, A. G. Dabak, Yan Hui and Gibong Jeong, in Proc. IEEE ICC, 2003, pp. 3205-3209. In this paper, two HARQ combining schemes are proposed at the receiver side, namely pre-combining and post-combining, the former being shown to be superior to the latter. In addition, a transmission technique, termed basis hopping, is presented which improves the HARQ diversity gain especially in slow fading channels. Pre-combining can be used in conjunction with the basis hopping technique.